Should I be scared of the bubble-ness of Nvidia? I have a lot of faith in the company and its vision, but reading about the bubble always scares me.
If scale is all you need, then we'll get there. But I'm not remotely convinced and see this as the bitter lesson's bitter lesson (a misinterpretation of the bitter lesson). But if we fund alternative pathways and hedge our bets, it's possible we get there without missing a step. But imo it looks like we've created a railroad and are just going all in on laying more tracks. Doesn't seem like the right move to me, but hey, I don't know the future any more than anyone else.
The share price of nvidia will collapse as soon as anyone else releases a competitive datacenter gpu. End of the day GPU compute is fully commoditized. Massive margins in commodity markets dont exist because competition leads to a race to the bottom in pricing. Hard for me to imagine that doesnt happen eventually, but wouldnt be surprised if it took 5 years.
I don’t what are you on about…
The company itself is great, and is making a ton of money. But the share price of Nvidia is absolutely pure speculative hype !
The math - in the past year, during which Nvidia suddenly found itself in a monopoly situation during a huge spike in AI interest (or / and hype), they made 60B$ in revenue (x2 from 2023), and 30B$ in net profit (x10 ! from 2023). Both numbers are huge. But ... the company is valued at 1800 B$ currently. There is this pesky little ratio that is sometimes useful, called price / earning ratio, and it gives a number around 60 here.
So in short - great company, perfect positioning, but way overpriced.
Or, just talk to your hiring manager(s) about the dilemma. For both companies, it'd be better to talk through any concerns before joining. If you accept one offer and then regret it a few months later, everyone loses: you, NVIDIA and [FAANG].
That being said, Nvidia will have a good 2-3 years in the future, until the cloud providers start mass replace their chips with in-house ones.
For money, unfortunately, it is as good as anyone's guess, but if you join now, double your share, it will be close to 4T. I personally didn't think that is sustainable amount of money if market/competition does their duty.
How do you imagine that happening on such a rapid timeline?
IMO, the biggest threat to Nvidia is radical innovation on the software side of AI that allows common use cases (training and inference) to run on clusters of commodity non-GPU hardware for cheaper price than GPU.
A similar threat is posed from ASIC chips that are dedicated to LLM tasks, but at least in that case Nvidia can still compete for a specific hardware design rather than overcoming an entire category of commodity hardware.
https://qz.com/intel-microsoft-new-chip-semiconductor-nvidia...
NVDA's margin is too high, it attracts competitors to eat into that.
Second, there is no need to be market leading, it just needs to be cost efficiently to be successful, even if it is slower, as long as it is cheaper. All cloud providers have huge chip design/manufacturing history, AWS/Azure and Google.
I would argue it IS indeed the core competency for those cloud providers, because of price. The inhouse chips exist because they can reduce the cost.
I know for a fact, there is huge momentum in some big clouds to replace Nvidia GPUs with their own chips, at least for their internal compute needs at first.
Also, if GPUs are easier to make than CPUs, then why isn't Intel leading the market in GPUs by now? Surely it's been clear they should compete with Nvidia there for at least the past half a decade. Or do they need more than 2-3 years to catch up?
I'm not disagreeing they can catch up within 10 years. But 2-3 years is an insane estimate IMO.
The beauty of being fabless is that they dont need to worry about that. When theyve got a design they like they just call TSMC and buy out all their capacity, they could pay double what nvidia does and still save a boatload. I agree that 2 years seems impossible and 3 a stretch, but I do think its possible for at least one cloud company to have something by then.
But also consider the reason Nvidia is doing so well in the first place. The reason is because they were already developing hardware that specialized at performing tensor operations. Maybe not at the size or always the same types we see in ML, but not very far either. There's reasons why they aren't filling cards with tensor cores. But they are clearly developing specialized hardware for ML tasks. I'm not sure betting on LLMs sticking around is the best bet though. I'll be very impressed if scale is all you need.
If NVDA has a position that fits you and you like the team, go for it! If you're just chasing money.. please don't.
Just sell shares when they vest to reduce your risk.
https://www.astralcodexten.com/p/sam-altman-wants-7-trillion